Preface |
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xiii | |
About the Authors |
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xix | |
1 Introduction to Operations Research |
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1 | (22) |
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1.1 The Origins and Applications of Operations Research |
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1 | (2) |
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1.2 System Modeling Principles |
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3 | (2) |
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1.3 Algorithm Efficiency and Problem Complexity |
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5 | (4) |
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1.4 Optimality and Practicality |
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9 | (1) |
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1.5 Software for Operations Research |
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10 | (4) |
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1.6 Illustrative Applications |
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14 | (4) |
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1.6.1 Analytical Innovation in the Food and Agribusiness Industries |
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14 | (1) |
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1.6.2 Humanitarian Relief in Natural Disasters |
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15 | (2) |
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1.6.3 Mining and Social Conflicts |
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17 | (1) |
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18 | (1) |
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19 | (1) |
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References and Suggested Readings |
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20 | (3) |
2 Linear Programming |
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23 | (66) |
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2.1 The Linear Programming Model |
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23 | (1) |
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2.2 The Art and Skill of Problem Formulation |
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24 | (6) |
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2.2.1 Integer and Nonlinear Models |
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30 | (1) |
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2.3 Graphical Solution of Linear Programming Problems |
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30 | (6) |
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2.3.1 General Definitions |
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30 | (1) |
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2.3.2 Graphical Solutions |
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31 | (2) |
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2.3.3 Multiple Optimal Solutions |
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33 | (1) |
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2.3.4 No Optimal Solution |
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34 | (1) |
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2.3.5 No Feasible Solution |
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35 | (1) |
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2.3.6 General Solution Method |
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36 | (1) |
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2.4 Preparation for the Simplex Method |
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36 | (3) |
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2.4.1 Standard Form of a Linear Programming Problem |
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36 | (2) |
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2.4.2 Solutions of Linear Systems |
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38 | (1) |
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39 | (7) |
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2.6 Initial Solutions for General Constraints |
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46 | (4) |
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2.6.1 Artificial Variables |
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46 | (2) |
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2.6.2 The Two Phase Method |
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48 | (2) |
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2.7 Information in the Tableau |
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50 | (6) |
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2.7.1 Multiple Optimal Solutions |
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51 | (1) |
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2.7.2 Unbounded Solution (No Optimal Solution) |
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51 | (2) |
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2.7.3 Degenerate Solutions |
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53 | (2) |
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2.7.4 Analyzing the Optimal Tableau: Shadow Prices |
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55 | (1) |
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2.8 Duality and Sensitivity Analysis |
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56 | (7) |
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56 | (4) |
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2.8.2 Postoptimality and Sensitivity Analysis |
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60 | (3) |
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2.9 Revised Simplex and Computational Efficiency |
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63 | (1) |
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2.10 Software for Linear Programming |
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64 | (7) |
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2.10.1 Extensions to General Simplex Methods |
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65 | (2) |
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67 | (2) |
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2.10.3 Software for Solving Linear Programming |
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69 | (2) |
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2.11 Illustrative Applications |
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71 | (3) |
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2.11.1 Forest Pest Control Program |
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71 | (1) |
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2.11.2 Aircraft and Munitions Procurement |
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72 | (1) |
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2.11.3 Grape Processing: Materials Planning and Production |
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73 | (1) |
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74 | (1) |
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75 | (1) |
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76 | (9) |
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References and Suggested Readings |
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85 | (4) |
3 Network Analysis |
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89 | (68) |
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3.1 Graphs and Networks: Preliminary Definitions |
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90 | (2) |
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3.2 Maximum Flow in Networks |
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92 | (5) |
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3.2.1 Maximum Flow Algorithm |
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93 | (3) |
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3.2.2 Extensions to the Maximum Flow Problem |
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96 | (1) |
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3.3 Minimum Cost Network Flow Problems |
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97 | (19) |
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3.3.1 Transportation Problem |
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97 | (12) |
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3.3.1.1 Northwest Corner Rule |
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99 | (2) |
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3.3.1.2 Minimum Cost Method |
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101 | (1) |
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3.3.1.3 Minimum "Row" Cost Method |
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102 | (1) |
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3.3.1.4 Transportation Simplex Method |
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103 | (4) |
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3.3.1.5 Transportation Simplex |
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107 | (2) |
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3.3.2 Assignment Problem and Stable Matching |
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109 | (5) |
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113 | (1) |
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3.3.3 Capacitated Transshipment Problem |
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114 | (2) |
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116 | (3) |
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3.4.1 Minimum Spanning Trees |
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116 | (2) |
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3.4.2 Shortest Network Problem: A Variation on Minimum Spanning Trees |
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118 | (1) |
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3.5 Shortest Path Problems |
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119 | (6) |
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3.5.1 Shortest Path through an Acyclic Network |
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120 | (1) |
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3.5.2 Shortest Paths from Source to All Other Nodes |
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121 | (2) |
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3.5.3 Problems Solvable with Shortest Path Methods |
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123 | (2) |
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125 | (7) |
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3.6.1 Labeling Method for Multi-Stage Decision Making |
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126 | (1) |
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127 | (3) |
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3.6.3 General Recursive Method |
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130 | (2) |
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132 | (9) |
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3.7.1 Project Networks and Critical Paths |
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133 | (4) |
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3.7.2 Cost versus Time Trade-Offs |
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137 | (2) |
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3.7.3 Probabilistic Project Scheduling |
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139 | (2) |
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3.8 Software for Network Analysis |
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141 | (1) |
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3.9 Illustrative Applications |
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142 | (2) |
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3.9.1 DNA Sequence Comparison Using a Shortest Path Algorithm |
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142 | (1) |
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3.9.2 Multiprocessor Network Traffic Scheduling |
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142 | (1) |
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3.9.3 Shipping Cotton from Farms to Gins |
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143 | (1) |
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144 | (1) |
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145 | (1) |
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146 | (8) |
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References and Suggested Readings |
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154 | (3) |
4 Integer Programming |
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157 | (60) |
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157 | (2) |
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4.2 Typical Integer Programming Problems |
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159 | (2) |
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4.2.1 General Integer Problems |
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159 | (1) |
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4.2.2 Zero-One (0-1) Problems |
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159 | (1) |
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4.2.3 Mixed Integer Problems |
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160 | (1) |
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4.3 Zero-One (0-1) Model Formulations |
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161 | (4) |
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4.3.1 Traveling Salesman Model |
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161 | (1) |
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162 | (1) |
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162 | (1) |
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4.3.4 Set Partitioning/Covering/Packing Models |
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163 | (1) |
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4.3.5 Generalized Assignment Model |
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164 | (1) |
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165 | (12) |
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165 | (4) |
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4.4.2 A Basic Branch-and-Bound Algorithm |
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169 | (1) |
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169 | (2) |
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4.4.4 From Basic Method to Commercial Code |
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171 | (16) |
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4.4.4.1 Branching Strategies |
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172 | (2) |
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4.4.4.2 Bounding Strategies |
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174 | (1) |
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175 | (1) |
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4.4.4.4 The Impact of Model Formulation |
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175 | (2) |
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4.4.4.5 Representation of Real Numbers |
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177 | (1) |
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4.5 Cutting Planes and Facets |
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177 | (3) |
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180 | (7) |
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4.7 Lagrangian Relaxation |
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187 | (10) |
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4.7.1 Relaxing Integer Programming Constraints |
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187 | (1) |
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188 | (3) |
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4.7.3 The Integrality Gap |
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191 | (1) |
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4.7.4 The Generalized Assignment Problem |
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192 | (2) |
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4.7.5 A Basic Lagrangian Relaxation Algorithm |
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194 | (1) |
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4.7.6 A Customer Allocation Problem |
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194 | (3) |
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197 | (4) |
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4.9 Software for Integer Programming |
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201 | (1) |
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4.10 Illustrative Applications |
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202 | (4) |
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4.10.1 Solid Waste Management |
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202 | (2) |
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4.10.2 Timber Harvest Planning |
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204 | (1) |
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4.10.3 Propane Bottling Plants |
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205 | (1) |
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206 | (1) |
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207 | (1) |
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208 | (5) |
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References and Suggested Readings |
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213 | (4) |
5 Nonlinear Optimization |
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217 | (32) |
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5.1 Preliminary Notation and Concepts |
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218 | (5) |
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5.2 Unconstrained Optimization |
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223 | (6) |
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5.2.1 One-Dimensional Search |
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223 | (2) |
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5.2.1.1 One-Dimensional Search Algorithm |
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223 | (2) |
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5.2.2 Multivariable Search: Gradient Method |
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225 | (3) |
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5.2.2.1 Multivariable Gradient Search |
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226 | (2) |
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228 | (1) |
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5.2.4 Quasi-Newton Methods |
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229 | (1) |
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5.3 Constrained Optimization |
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229 | (7) |
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5.3.1 Lagrange Multipliers (Equality Constraints) |
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229 | (1) |
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5.3.2 Karush-Kuhn-Tucker Conditions (Inequality Constraints) |
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230 | (1) |
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5.3.3 Quadratic Programming |
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231 | (5) |
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5.3.4 More Advanced Methods |
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236 | (1) |
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5.4 Software for Nonlinear Optimization |
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236 | (3) |
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5.5 Illustrative Applications |
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239 | (3) |
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5.5.1 Gasoline Blending Systems |
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239 | (1) |
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5.5.2 Portfolio Construction |
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240 | (1) |
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5.5.3 Balancing Rotor Systems |
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241 | (1) |
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242 | (1) |
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242 | (1) |
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243 | (2) |
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References and Suggested Readings |
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245 | (4) |
6 Markov Processes |
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249 | (36) |
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250 | (6) |
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256 | (3) |
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6.3 First Passage Probabilities |
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259 | (2) |
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6.4 Properties of the States in a Markov Process |
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261 | (2) |
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6.5 Steady-State Analysis |
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263 | (2) |
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6.6 Expected First Passage Times |
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265 | (2) |
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267 | (4) |
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6.8 Software for Markov Processes |
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271 | (1) |
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6.9 Illustrative Applications |
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272 | (4) |
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6.9.1 Water Reservoir Operations |
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272 | (1) |
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6.9.2 Markov Analysis of Dynamic Memory Allocation |
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273 | (1) |
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6.9.3 Markov Models for Manufacturing Production Capability |
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274 | (1) |
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6.9.4 Markov Decision Processes in Dairy Farming |
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275 | (1) |
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276 | (1) |
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276 | (1) |
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277 | (4) |
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References and Suggested Readings |
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281 | (4) |
7 Queueing Models |
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285 | (26) |
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7.1 Basic Elements of Queueing Systems |
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285 | (3) |
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7.2 Arrival and Service Patterns |
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288 | (3) |
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7.2.1 The Exponential Distribution |
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288 | (2) |
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7.2.2 Birth-and-Death Processes |
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290 | (1) |
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7.3 Analysis of Simple Queueing Systems |
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291 | (8) |
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7.3.1 Notation and Definitions |
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291 | (1) |
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7.3.2 Steady State Performance Measures |
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292 | (6) |
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7.3.3 Practical Limits of Queueing Models |
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298 | (1) |
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7.4 Software for Queueing Models |
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299 | (1) |
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7.5 Illustrative Applications |
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300 | (5) |
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7.5.1 Cost Efficiency and Service Quality in Hospitals |
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300 | (2) |
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7.5.2 Queueing Models in Manufacturing |
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302 | (2) |
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7.5.3 Nurse Staffing Based on Queueing Models |
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304 | (1) |
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305 | (1) |
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306 | (1) |
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306 | (3) |
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References and Suggested Readings |
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309 | (2) |
8 Simulation |
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311 | (30) |
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8.1 Simulation: Purposes and Applications |
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311 | (3) |
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8.2 Discrete Simulation Models |
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314 | (7) |
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8.2.1 Event-Driven Models |
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314 | (3) |
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8.2.2 Generating Random Events |
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317 | (4) |
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8.3 Observations of Simulations |
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321 | (4) |
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8.3.1 Gathering Statistics |
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321 | (3) |
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8.3.1.1 Average Time in System |
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321 | (1) |
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8.3.1.2 Average Waiting Time |
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322 | (1) |
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8.3.1.3 Average Number in Queue |
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322 | (1) |
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8.3.1.4 Server Utilization |
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323 | (1) |
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8.3.2 Design of Simulation Experiments |
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324 | (1) |
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8.4 Software for Simulation |
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325 | (3) |
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8.5 Illustrative Applications |
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328 | (6) |
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8.5.1 Finnish Air Force Fleet Maintenance |
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328 | (1) |
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8.5.2 Simulation of a Semiconductor Manufacturing Line |
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329 | (2) |
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8.5.3 Simulation of Eurotunnel Terminals |
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331 | (1) |
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8.5.4 Simulation for NASA's Space Launch Vehicles Operations |
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332 | (2) |
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334 | (1) |
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334 | (1) |
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335 | (2) |
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References and Suggested Readings |
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337 | (4) |
9 Decision Analysis |
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341 | (54) |
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9.1 The Decision-Making Process |
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341 | (4) |
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9.2 An Introduction to Game Theory |
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345 | (5) |
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345 | (1) |
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346 | (1) |
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9.2.3 Laplace Principle (Principle of Insufficient Reason) |
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346 | (1) |
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346 | (1) |
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9.2.5 Savage Minimax Regret |
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347 | (3) |
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350 | (8) |
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358 | (12) |
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9.4.1 The Axioms of Utility Theory |
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359 | (2) |
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361 | (5) |
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9.4.3 The Shape of the Utility Curve |
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366 | (4) |
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9.5 The Psychology of Decision-Making |
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370 | (8) |
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9.5.1 Misconceptions of Probability |
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370 | (2) |
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372 | (1) |
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9.5.3 Anchoring and Adjustment |
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372 | (1) |
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9.5.4 Dissonance Reduction |
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373 | (1) |
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374 | (2) |
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9.5.6 The Sunk Cost Fallacy |
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376 | (1) |
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9.5.7 Irrational Human Behavior |
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377 | (2) |
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9.5.7.1 What Can We Do about Irrational Behavior? |
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378 | (1) |
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9.6 Software for Decision Analysis |
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378 | (1) |
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9.7 Illustrative Applications |
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379 | (6) |
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9.7.1 Decision Support System for Minimizing Costs in the Maritime Industry |
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379 | (2) |
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9.7.2 Refinery Pricing under Uncertainty |
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381 | (2) |
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9.7.3 Decisions for Radioactive Waste Management |
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383 | (1) |
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9.7.4 Investment Decisions and Risk in Petroleum Exploration |
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383 | (2) |
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385 | (1) |
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385 | (2) |
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387 | (5) |
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References and Suggested Readings |
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392 | (3) |
10 Heuristic and Metaheuristic Techniques for Optimization |
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395 | (38) |
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397 | (1) |
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10.2 Local Improvement Heuristics |
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398 | (2) |
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400 | (7) |
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407 | (2) |
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409 | (5) |
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414 | (3) |
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10.7 Constraint Programming and Local Search |
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417 | (1) |
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10.8 Other Metaheuristics |
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418 | (1) |
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10.9 Software for Metaheuristics |
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419 | (1) |
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10.10 Illustrative Applications |
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420 | (6) |
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10.10.1 FedEx Flight Management Using Simulated Annealing |
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420 | (2) |
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10.10.2 Ecosystem Management Using Genetic Algorithm Heuristics |
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422 | (2) |
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10.10.3 Efficient Routing and Delivery of Meals on Wheels |
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424 | (2) |
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426 | (1) |
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427 | (1) |
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428 | (2) |
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References and Suggested Readings |
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430 | (3) |
Appendix: Review of Essential Mathematics-Notation, Definitions, and Matrix Algebra |
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433 | (6) |
Index |
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439 | |